规范化(社会学)
预处理器
指数
信号(编程语言)
传感器阵列
生物系统
幂律
分析化学(期刊)
模式识别(心理学)
数学
化学
计算机科学
统计
人工智能
色谱法
生物
人类学
哲学
社会学
语言学
程序设计语言
作者
Joachim Goschnick,V. Magapu,I. Kiselev,Ilona Koronczi
标识
DOI:10.1016/j.snb.2005.12.067
摘要
Sample recognition with a metal oxide gas sensor array is often affected by a signal pattern dependence on the gas concentration, that blurs the class representation. The reason are differences of the sensor elements in the exponent of the power law that governs the concentration dependence of signals of the array elements. Under the power law the standard pattern normalization procedure using signal ratios eliminates the concentration dependence only if the two signals have the same power law exponent. A simple signal preprocessing algorithm is presented, which is able to suppress the differences in the non-linear concentration dependence of the array elements whereby concentration independent signal patterns can be obtained. Thereby the resolution of the pattern discrimination can be significantly improved resulting in improved gas recognition appropriate for a broad concentration range.
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